Concurrent Programming in Python

Name: Concurrent Programming in Python
Rating: 3.5 (11 reviews)

Harness the power of modern code structures with Python to improve performance and flexibility

Created byPackt Publishing

Last updated 3/2018

English

What you'll learn

Increase your awareness of concurrency in Python
Distinguish between parallel programming and concurrent programming
Explore Python's threading module
Familiarize yourself with Python's Global Interpreter Lock (GIL)
Master the similarities between thread and process management
Practice with open source Libraries
Learn process synchronization and inter-process communication
Work with best practices and caveats

Course content

6 sections • 25 lectures • 2h 20m total length

The Course Overview6:26
This video will give you an overview about the course.
Advanced OSes and Programming Environments8:19
Get familiar and introduced to evolution of computing hardware, advancement of OSes and programmer’s interface to concurrency.
Concurrency Versus Parallelism with Examples2:24
Learn about the difference between concurrency and parallelism and view an example.
Operating System’s Building Blocks of Parallel Execution2:20
Get introduced to operating system blocks for parallel execution like process, thread, etc.
Libraries in Python Used to Achieve Concurrency and Parallelism2:20
Learn about threading, multiprocessing and queue concepts.
Python’s Global Interpreter Lock (GIL)6:28
Learn about the Python’s Global Interpreter Lock.

Synchronization in Python5:56
Introduce thread synchronization and various synchronization primitives and learn when and how to use them.
Using Synchronization Primitives5:14
Learn about what happens if we don’t use synchronization and also how to use Lock and RLock synchronization primitives.
Producer–Consumer Pattern6:09
Get introduced to producer-consumer pattern with a demo of a working producer-consumer program and look into how to synchronize the producer and consumer threads using the Event class.
Using Python Queue Module4:30
Learn about Queue class and its various feature and watch a code demo of how the queue class can help us solve produce-consumer problem.
Multithreading in GUI Programming3:29
Explore some GUI examples of multi-threaded applications and learn What happens if we do not use multiple threads in a GUI application and how responsiveness can be improved with multiple threads.

Limitations Imposed by GIL4:49
Learn about the limitations imposed by GIL to python multithreading and how to overcome these limitations.
Multiprocessing11:31
Learn about multiprocessing module and creating subprocesses using this module and comparing multiprocessing and multithreading.
Similarities Between Thread and Process Management3:20
Explore the similarities between thread and process management.
Difference Between Thread and Process Management8:15
Learn the differences between thread and process management.
Libraries for Practice4:21
Explore the open source libraries for multithreading and multiprocessing.

Pool of Workers for Maximizing Usage of the Hardware5:06
Learn about the constraints of multiprocessing and how to overcome those through a real-world example.
When and How to Use a Pool of Workers5:04
Get introduced to the multiprocessing Pool class and learn when how to use the pool of workers through a real-world usage of it.
Best Practices and Anti-Patterns6:04
Get introduced to some good practices and anti-patterns while using multiprocessing.

Requirements

Basic knowledge on python programing

Description

In this course, you will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing.

Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing.

After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.

About the Author

BignumWorks Software LLP is an India-based software consultancy that provides consultancy services in the area of software development and technical training. Our domain expertise includes web, mobile, cloud app development, data science projects, in-house software training services, and up-skilling services

Who this course is for:

Python developers who want to learn how to write concurrent applications to speed up the execution of their programs, and to provide interactivity for users, will greatly benefit from this course.

Concurrent Programming in Python

What you'll learn

Explore related topics

Course content

Introduction to Concurrent Programming6 lectures • 28min

Creating and Managing Threads3 lectures • 20min

Thread Synchronization Primitives5 lectures • 25min

Creating and Managing Processes5 lectures • 32min

Synchronization and Inter-Process Communication3 lectures • 18min

Using a Pool of Workers3 lectures • 16min

Requirements

Description

Who this course is for: